Expression of Ferroptosis-Related Genes is Correlated with Immune Microenvironment in Diabetic Kidney Disease

Abstract

Objective

This study aims to explore the correlation between ferroptosis and immune microenvironment (IME) in diabetic kidney disease (DKD) to provide a new clue for exploring the underlying molecular mechanisms.

Methods

Corresponding RNA data of DKD patients were downloaded from GEO databases. The weighted gene co-expression network analysis (WGCNA) was used to construct the network, and the selected hub genes, then, overlapped with ferroptosis-related genes (FRGs) from FerrDb. Consensus clustering was performed to identify new molecular subgroups. ESTIMATE, TIMER and ssGSEA analyses were applied to determinate the IME and immune status. Functional analyses including GO, KEGG and GSEA were conducted to elucidate the underlying mechanisms.

Results

Two molecular subtypes were identified based on the expression of FRGs. ESTIMATE algorithm revealed that there were significant differences in ESTIMATE score between these two clusters of DKD patients, with no significant difference found in stromal score and immune score. In addition, TIMER algorithm indicated there was a significant difference in the degree of T cell infiltration. The ssGSEA algorithm showed immunity was mainly concentrated in thick ascending limb and distal convoluted tubule in adult kidney. GO, KEGG and GSEA analyses revealed that the differentially expressed genes (DEGs) were mainly enriched in immune and metabolism associated pathways.

Conclusion

The ferroptosis may be induced by dysregulation of IME, thereby accelerating the progression of DKD. Our work could be applied to provide a new clue for exploring the underlying molecular mechanisms and sheds novel light on the therapy strategy of DKD.

Keywords:

• diabetic kidney disease
• DKD
• ferroptosis
• immune microenvironment
• IME
• metabolism

Data Sharing Statement

The data that support the findings of this study are openly available in GEO (https://www.ncbi.nlm.nih.gov/gds/).

Statement of Ethics

According to the Ethics Committee of Zhongnan Hospital of Wuhan University, the analysis of the data from the public database does not involve the collection of biological samples, which can be exempt from approval.

Author Contributions

All authors contributed to data analysis, drafting or revising the article, have agreed on the journal to which the article will be submitted, gave final approval of the version to be published, and agree to be accountable for all aspects of the work.

Disclosure

The authors declare that they have no competing interests in this work.

Additional information

Funding

This work was supported by grants from the National Natural Science Foundation of China (82200807, 82100763, 82100721and 81900698), Hubei Provincial Natural Science Foundation of China (2021CFB090), China Postdoctoral Science Foundation (2022M710686) and the Foundation of Jiangsu Commission of Health (M2021048), the Fundamental Research Funds for the Central University (2042021kf0150 and 2042020kf0137), Zhongnan Hospital of Wuhan University Science, Technology and Innovation Seed Fund, Project (cxpy2020027 and znpy2019036). Excellent Doctor (Post), Zhongnan Hospital of Wuhan University (ZNYB2020009), Zhongnan Hospital of Wuhan University Science, Technology and Innovation Seed Fund, Project znpy2019036 and znpy2017044. Hubei Province Health and Family Planning Scientific Research Project (WJ2019MB103). The Clinical Research Project for Wu Jieping Medical Foundation (320.6750.19089-58). The Research Fund from Medical Sci-Tech Innovation Platform of Zhongnan Hospital, Wuhan University (PTXM2020028 and XKJS202035).